Asymptotic properties of maximum likelihood estimator for the growth rate of a stable CIR process based on continuous time observations - Normandie Université Accéder directement au contenu
Article Dans Une Revue Statistics Année : 2019

Asymptotic properties of maximum likelihood estimator for the growth rate of a stable CIR process based on continuous time observations

Résumé

We consider a stable Cox--Ingersoll--Ross process driven by a standard Wiener process and a spectrally positive strictly stable L\'evy process, and we study asymptotic properties of the maximum likelihood estimator (MLE) for its growth rate based on continuous time observations. We distinguish three cases: subcritical, critical and supercritical. In all cases we prove strong consistency of the MLE in question, in the subcritical case asymptotic normality, and in the supercritical case asymptotic mixed normality are shown as well. In the critical case the description of the asymptotic behavior of the MLE in question remains open.
Fichier principal
Vignette du fichier
Barczy_BenAlaya_Kebaier_Pap_2019_arxiv.pdf (541.21 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-02332449 , version 1 (13-02-2024)

Identifiants

Citer

Matyas Barczy, Mohamed Ben Alaya, Ahmed Kebaier, Gyula Pap. Asymptotic properties of maximum likelihood estimator for the growth rate of a stable CIR process based on continuous time observations. Statistics, 2019, 53 (3), pp.533-568. ⟨10.1080/02331888.2019.1579216⟩. ⟨hal-02332449⟩
79 Consultations
0 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More